1. Field of the Invention
This invention relates to illumination normalization of digital images, and more particularly, to methods and apparatuses for using various types of diffusion processing for removing intensity variations in an image which are caused by illumination.
2. Description of the Related Art
Images may contain variations in intensity which are introduced by the light source used to illuminate the subject and/or scene composing the image. These intensity variations may be undesirable because not only can they be visually distracting and reduce the aesthetic quality of an image, but they may also pose difficulties for various types of image processing algorithms, such as, for example, algorithms used for automatic facial recognition. These variations may manifest themselves in the form of edge artifacts, which are referred to herein as spurious edges. Spurious edges can be quite distracting because they can mask real edges in the image, where real edges, which are the result of the underling structure of the subject or scene within the image, contain information typically of most interest to image users. Spurious edges, as well as other undesirable illumination variations, can be corrected through the use of illumination normalization techniques.
Conventional illumination normalization techniques include level compression techniques to mitigate the appearance of illumination variations. Some level compression techniques use logarithmic functions to compress the dynamic range of the image, thus reducing the perception illumination gradients. Other techniques may use statistical approaches such as histogram stretching or equalization. Histogram approaches may seek to alter the intensity distribution of the image to improve overall contrast and reduce the effect of unwanted variations in intensity due to illumination. However, such conventional techniques may have difficulty compensating for sharp spurious edges, and may further cause other global variations in intensity which may be undesirable. Accordingly, there is a need for approaches to reduce spurious edges in digital images without affecting other portions therein in a detrimental manner.